This application provides a method, apparatus, electronic device, computer-readable storage medium, and
computer program product for predicting the health of tightening equipment. The method includes: obtaining a batch of tightening samples of a target tightening equipment from a preset sample trend
library; obtaining target sample drift characteristics of the target tightening equipment based on the batch tightening samples and a preset
standard template library; obtaining target equipment drift characteristics of the target tightening equipment based on a first normal sample of the batch tightening samples and the preset
standard template library; when the number of abnormal samples in the batch tightening samples exceeds a preset threshold, performing a health prediction based on the target sample drift characteristics and the target equipment drift characteristics to obtain a health prediction result. Abnormal samples refer to workpiece samples with abnormal process inspection results. The health prediction result includes at least one of the following: abnormal
component type, abnormal confidence level, and abnormal level. This application can predict potential abnormalities in tightening equipment in advance, improving the accuracy of equipment health prediction results.